GLM 5 vs LongCat-2.5
Z.ai · China | Meituan · China · Updated June 2026
Quick verdict
Pick GLM 5 for agentic planning and long-horizon coding workflows or complex systems design and backend reasoning. Pick LongCat-2.5 for native multimodal upgrade to longcat-2.0 - 1.6t total parameters, about 48b active per token or limited-time api price of $0.30/$1.20 per million tokens (cached input $0.006). Choose GLM 5 if you need self-hosting or data privacy; LongCat-2.5 if you want a managed API.
GLM 5 (Z.ai) and LongCat-2.5 (Meituan) are two of the models people most often weigh against each other in 2026. GLM 5 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. LongCat-2.5 is meituan's November 2, 2026 natively multimodal successor to LongCat-2.0 - 1.6T parameters and 1M context at $0.30/$1.20, with open weights planned but undated. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: LongCat-2.5 is about 3.3× cheaper on input ($0.3/$1.2 per 1M tokens vs $1/$3.2 per 1M tokens) — meaningful once you are processing millions of tokens a month.
- ▸Context window: LongCat-2.5 holds 5× more — 1M tokens (~1,500 pages) vs 200K (~300 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: LongCat-2.5 is the newer model by about 9 months (released November 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | GLM 5 | LongCat-2.5 |
|---|---|---|
| Provider | Z.ai (China) | Meituan (China) |
| Released | February 12, 2026 | November 2, 2026 |
| Context window | 200K (~300 pages) | 1M tokens (~1,500 pages) |
| Price (in/out) | $1/$3.2 per 1M tokens | $0.3/$1.2 per 1M tokens |
| Open weight? | Yes — self-hostable | No — API only |
| Modalities | text, code | text, image, code |
| SWE-Bench Verified | 77.8% | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Agentic planning and long-horizon coding workflows
GLM 5
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding — and its weights are open while LongCat-2.5 is API-only.
Complex systems design and backend reasoning
GLM 5
GLM 5 lists complex systems design and backend reasoning among its strengths; LongCat-2.5 does not.
Iterative self-correction on autonomous tasks
GLM 5
GLM 5 lists iterative self-correction on autonomous tasks among its strengths; LongCat-2.5 does not.
Native multimodal upgrade to LongCat-2.0 - 1.6T total parameters, about 48B active per token
LongCat-2.5
Its 1M tokens window holds about 5× more than GLM 5's 200K in a single prompt.
Limited-time API price of $0.30/$1.20 per million tokens (cached input $0.006)
LongCat-2.5
At $0.3/$1.2 per 1M tokens it undercuts GLM 5 ($1/$3.2 per 1M tokens), and that gap compounds at volume.
Meituan-reported Terminal-Bench v2.1 of 88.4, up from 70.8 for LongCat-2.0
LongCat-2.5
Meituan's November 2, 2026 natively multimodal successor to LongCat-2.0 - 1.6T parameters and 1M context at $0.30/$1.20, with open weights planned but undated — and it runs cheaper at $0.3/$1.2 per 1M tokens.
Lowest cost at scale
LongCat-2.5
At $0.3/$1.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
LongCat-2.5
Its 1M tokens window is about 5× larger than GLM 5's 200K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ LongCat-2.5
At $0.3/$1.2 per 1M tokens it undercuts GLM 5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ LongCat-2.5
Larger 1M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ GLM 5
Open weights let you run it on your own hardware; LongCat-2.5 is API-only.
Anyone whose priority is agentic planning and long-horizon coding workflows
→ GLM 5
It is specifically built for that.
Anyone whose priority is native multimodal upgrade to longcat-2.0 - 1.6t total parameters, about 48b active per token
→ LongCat-2.5
That is its strongest area.
GLM 5: where it fits
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. Released February 12, 2026 by Z.ai, it is built for agentic planning and long-horizon coding workflows, complex systems design and backend reasoning, iterative self-correction on autonomous tasks, and open weights under the permissive MIT license.
Its trade-offs are real: 200K context trails 1M-context rivals, and quickly superseded by GLM-5.1 and GLM-5.2. At $1 in / $3.2 out per million tokens, it sits in the budget price band.
LongCat-2.5: where it fits
Meituan's November 2, 2026 natively multimodal successor to LongCat-2.0 - 1.6T parameters and 1M context at $0.30/$1.20, with open weights planned but undated. Released November 2, 2026 by Meituan, it is built for native multimodal upgrade to LongCat-2.0 - 1.6T total parameters, about 48B active per token, limited-time API price of $0.30/$1.20 per million tokens (cached input $0.006), meituan-reported Terminal-Bench v2.1 of 88.4, up from 70.8 for LongCat-2.0, and openAI- and Anthropic-compatible API endpoints with a 1M-token context window.
Its trade-offs: aPI-only for now - GitHub and Hugging Face releases are planned but undated, and the license is unconfirmed (LongCat-2.0 is MIT), the $0.30/$1.20 rate is labeled limited-time, and Meituan says prices are subject to change, and benchmarks are Meituan's own, and sources found no independent score at launch. At $0.3 in / $1.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. GLM 5 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. LongCat-2.5 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both GLM 5 and LongCat-2.5 without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
See pricingFrequently asked questions
Is GLM 5 or LongCat-2.5 better for coding?
Public SWE-Bench figures are not available for LongCat-2.5, so the honest test is your own repository — run an identical real bug through both. By design, GLM 5 leans toward agentic planning and long-horizon coding workflows while LongCat-2.5 leans toward native multimodal upgrade to longcat-2.0 - 1.6t total parameters, about 48b active per token, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5 or LongCat-2.5?
GLM 5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while LongCat-2.5 is API-metered at $0.3/$1.2 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
LongCat-2.5 — 1M tokens vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GLM 5 and LongCat-2.5 together?
Yes — a multi-model platform like LumiChats gives you GLM 5, LongCat-2.5 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, GLM 5 or LongCat-2.5?
LongCat-2.5 — released November 2, 2026, about 9 months after GLM 5.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.